Pandas Profiling Report

Dataset statistics

Number of variables	49
Number of observations	483
Missing cells	681
Missing cells (%)	2.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	185.0 KiB
Average record size in memory	392.3 B

Variable types

Numeric	9
Categorical	39
DateTime	1

Warnings

`GR_POD` has constant value "1"	Constant
`ENTE` has a high cardinality: 480 distinct values	High cardinality
`POP` is highly correlated with `TAM.ATV` and 1 other fields	High correlation
`TAM.ATV` is highly correlated with `POP` and 1 other fields	High correlation
`GR_C.ÉT` is highly correlated with `CIE_REL` and 3 other fields	High correlation
`CIE_REL` is highly correlated with `GR_C.ÉT` and 2 other fields	High correlation
`GI_COMITÊ` is highly correlated with `LI_DIR.CERT`	High correlation
`GTI_POL.INFR.` is highly correlated with `GR_C.ÉT` and 1 other fields	High correlation
`RP_REL.GOV` is highly correlated with `GR_C.ÉT` and 2 other fields	High correlation
`LI_DIR.CERT` is highly correlated with `GI_COMITÊ`	High correlation
`LI_P.EST.` is highly correlated with `GR_C.ÉT` and 3 other fields	High correlation
`R.FIN` is highly correlated with `R.AT`	High correlation
`IND.SF` is highly correlated with `IND.COB`	High correlation
`R.INV` is highly correlated with `TAM.ATV`	High correlation
`R.AT` is highly correlated with `POP` and 1 other fields	High correlation
`IND.COB` is highly correlated with `IND.SF`	High correlation
`POP` is highly correlated with `TAM.ATV` and 2 other fields	High correlation
`TAM.ATV` is highly correlated with `POP` and 2 other fields	High correlation
`GR_C.ÉT` is highly correlated with `CIE_REL` and 3 other fields	High correlation
`CIE_REL` is highly correlated with `GR_C.ÉT` and 2 other fields	High correlation
`GI_COMITÊ` is highly correlated with `LI_DIR.CERT`	High correlation
`GTI_POL.INFR.` is highly correlated with `GR_C.ÉT` and 1 other fields	High correlation
`RP_REL.GOV` is highly correlated with `GR_C.ÉT` and 2 other fields	High correlation
`LI_DIR.CERT` is highly correlated with `GI_COMITÊ`	High correlation
`LI_P.EST.` is highly correlated with `GR_C.ÉT` and 3 other fields	High correlation
`R.FIN` is highly correlated with `IND.SF` and 1 other fields	High correlation
`IND.SF` is highly correlated with `R.FIN` and 1 other fields	High correlation
`R.INV` is highly correlated with `POP` and 2 other fields	High correlation
`R.AT` is highly correlated with `POP` and 3 other fields	High correlation
`IND.COB` is highly correlated with `R.FIN` and 2 other fields	High correlation
`POP` is highly correlated with `R.AT`	High correlation
`TAM.ATV` is highly correlated with `R.INV`	High correlation
`GR_C.ÉT` is highly correlated with `CIE_REL` and 3 other fields	High correlation
`CIE_REL` is highly correlated with `GR_C.ÉT` and 2 other fields	High correlation
`GI_COMITÊ` is highly correlated with `LI_DIR.CERT`	High correlation
`GTI_POL.INFR.` is highly correlated with `GR_C.ÉT` and 1 other fields	High correlation
`RP_REL.GOV` is highly correlated with `GR_C.ÉT` and 2 other fields	High correlation
`LI_DIR.CERT` is highly correlated with `GI_COMITÊ`	High correlation
`LI_P.EST.` is highly correlated with `GR_C.ÉT` and 3 other fields	High correlation
`R.FIN` is highly correlated with `IND.SF`	High correlation
`IND.SF` is highly correlated with `R.FIN`	High correlation
`R.INV` is highly correlated with `TAM.ATV`	High correlation
`R.AT` is highly correlated with `POP`	High correlation
`RP_REG.ENV` is highly correlated with `GI_C.TÉC` and 4 other fields	High correlation
`GI_C.TÉC` is highly correlated with `RP_REG.ENV` and 3 other fields	High correlation
`UF` is highly correlated with `RP_REG.ENV` and 10 other fields	High correlation
`PS_GEST` is highly correlated with `UF`	High correlation
`R.FIN` is highly correlated with `R.INV` and 3 other fields	High correlation
`R.INV` is highly correlated with `UF` and 4 other fields	High correlation
`CIE_FISC` is highly correlated with `GI_DIV.CART` and 3 other fields	High correlation
`GI_COMITÊ` is highly correlated with `GI_C.TÉC` and 1 other fields	High correlation
`VAR.INV` is highly correlated with `R.AT`	High correlation
`AD.PROG` is highly correlated with `Nº`	High correlation
`C.PROG` is highly correlated with `UF` and 4 other fields	High correlation
`GI_DIV.CART` is highly correlated with `CIE_FISC` and 3 other fields	High correlation
`DDM_CART` is highly correlated with `Nº`	High correlation
`RP_SITE` is highly correlated with `N.JUR` and 1 other fields	High correlation
`POP` is highly correlated with `R.INV` and 4 other fields	High correlation
`REGIÃO` is highly correlated with `UF`	High correlation
`CIE_REL` is highly correlated with `Nº` and 5 other fields	High correlation
`SA_PUB.REL` is highly correlated with `RP_REG.ENV` and 6 other fields	High correlation
`R.AT` is highly correlated with `R.FIN` and 5 other fields	High correlation
`Nº` is highly correlated with `AD.PROG` and 7 other fields	High correlation
`DDM_ATAS` is highly correlated with `CIE_REL` and 4 other fields	High correlation
`TAM.ATV` is highly correlated with `UF` and 6 other fields	High correlation
`SA_REPAS` is highly correlated with `RP_REG.ENV` and 4 other fields	High correlation
`N.JUR` is highly correlated with `UF` and 1 other fields	High correlation
`GTI_INV.TI` is highly correlated with `Nº`	High correlation
`MassaSeg.` is highly correlated with `UF` and 5 other fields	High correlation
`PRT_massa` is highly correlated with `UF` and 5 other fields	High correlation
`GTI_POL.INFR.` is highly correlated with `CIE_REL` and 3 other fields	High correlation
`LI_DIR.CERT` is highly correlated with `GI_COMITÊ`	High correlation
`CIE_CRP` is highly correlated with `RP_REG.ENV` and 6 other fields	High correlation
`GI_P.INV` is highly correlated with `C.PROG`	High correlation
`LI_P.EST.` is highly correlated with `C.PROG` and 5 other fields	High correlation
`GR_C.ÉT` is highly correlated with `C.PROG` and 6 other fields	High correlation
`PS_OUV` is highly correlated with `RP_SITE` and 1 other fields	High correlation
`RP_REL.GOV` is highly correlated with `CIE_REL` and 3 other fields	High correlation
`CIE_AUD` is highly correlated with `POP`	High correlation
`RP_REG.ENV` is highly correlated with `GR_POD`	High correlation
`GI_C.TÉC` is highly correlated with `GI_COMITÊ` and 2 other fields	High correlation
`UF` is highly correlated with `PS_GEST` and 2 other fields	High correlation
`PS_GEST` is highly correlated with `UF` and 1 other fields	High correlation
`CIE_FISC` is highly correlated with `GR_POD`	High correlation
`GI_COMITÊ` is highly correlated with `GI_C.TÉC` and 2 other fields	High correlation
`GR_SEGR` is highly correlated with `GR_POD`	High correlation
`AD.PROG` is highly correlated with `GR_C.ÉT` and 1 other fields	High correlation
`C.PROG` is highly correlated with `DDM_ACES` and 4 other fields	High correlation
`GI_DIV.CART` is highly correlated with `SA_REPAS` and 1 other fields	High correlation
`SA_AMRTZ` is highly correlated with `GR_POD`	High correlation
`DDM_CART` is highly correlated with `GR_POD`	High correlation
`RP_SITE` is highly correlated with `GR_POD`	High correlation
`REGIÃO` is highly correlated with `UF` and 1 other fields	High correlation
`CIE_REL` is highly correlated with `LI_P.EST.` and 3 other fields	High correlation
`SA_PUB.REL` is highly correlated with `CIE_CRP` and 1 other fields	High correlation
`DDM_ATAS` is highly correlated with `GR_POD`	High correlation
`SA_REPAS` is highly correlated with `GI_DIV.CART` and 1 other fields	High correlation
`N.JUR` is highly correlated with `GR_POD`	High correlation
`IP_SELEC` is highly correlated with `GR_POD`	High correlation
`GTI_INV.TI` is highly correlated with `GR_POD`	High correlation
`DDM_ACES` is highly correlated with `C.PROG` and 1 other fields	High correlation
`MassaSeg.` is highly correlated with `PRT_massa` and 1 other fields	High correlation
`PRT_massa` is highly correlated with `MassaSeg.` and 1 other fields	High correlation
`GTI_POL.INFR.` is highly correlated with `LI_P.EST.` and 2 other fields	High correlation
`LI_DIR.CERT` is highly correlated with `GI_C.TÉC` and 2 other fields	High correlation
`CIE_CRP` is highly correlated with `SA_PUB.REL` and 1 other fields	High correlation
`GI_P.INV` is highly correlated with `C.PROG` and 1 other fields	High correlation
`IP_REP.CF` is highly correlated with `GR_POD`	High correlation
`SA_R.ALIQ` is highly correlated with `GR_POD`	High correlation
`LI_P.EST.` is highly correlated with `C.PROG` and 5 other fields	High correlation
`GR_C.ÉT` is highly correlated with `AD.PROG` and 6 other fields	High correlation
`PS_OUV` is highly correlated with `GR_POD`	High correlation
`GI_CONS` is highly correlated with `GR_POD`	High correlation
`RP_REL.GOV` is highly correlated with `CIE_REL` and 3 other fields	High correlation
`LI_CERT.MB` is highly correlated with `GR_POD`	High correlation
`CIE_AUD` is highly correlated with `GR_POD`	High correlation
`GR_POD` is highly correlated with `RP_REG.ENV` and 36 other fields	High correlation
`N.JUR` has 10 (2.1%) missing values	Missing
`POP` has 27 (5.6%) missing values	Missing
`TAM.ATV` has 24 (5.0%) missing values	Missing
`C.PROG` has 283 (58.6%) missing values	Missing
`GI_CONS` has 12 (2.5%) missing values	Missing
`SA_REPAS` has 5 (1.0%) missing values	Missing
`DDM_ATAS` has 5 (1.0%) missing values	Missing
`RP_REL.GOV` has 5 (1.0%) missing values	Missing
`IP_REP.CF` has 16 (3.3%) missing values	Missing
`LI_CERT.MB` has 16 (3.3%) missing values	Missing
`R.FIN` has 30 (6.2%) missing values	Missing
`IND.SF` has 29 (6.0%) missing values	Missing
`R.INV` has 23 (4.8%) missing values	Missing
`VAR.INV` has 24 (5.0%) missing values	Missing
`R.AT` has 70 (14.5%) missing values	Missing
`IND.COB` has 70 (14.5%) missing values	Missing
`Nº` is uniformly distributed	Uniform
`ENTE` is uniformly distributed	Uniform
`Nº` has unique values	Unique
`IND.SF` has 6 (1.2%) zeros	Zeros

Reproduction

Analysis started	2021-05-25 22:21:37.221714
Analysis finished	2021-05-25 22:22:56.970360
Duration	1 minute and 19.75 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

Nº
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	483
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	242

Minimum	1
Maximum	483
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.9 KiB

Quantile statistics

Minimum	1
5-th percentile	25.1
Q1	121.5
median	242
Q3	362.5
95-th percentile	458.9
Maximum	483
Range	482
Interquartile range (IQR)	241

Descriptive statistics

Standard deviation	139.5743529
Coefficient of variation (CV)	0.5767535246
Kurtosis	-1.2
Mean	242
Median Absolute Deviation (MAD)	121
Skewness	0
Sum	116886
Variance	19481
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	0.2%
363	1	0.2%
331	1	0.2%
330	1	0.2%
329	1	0.2%
328	1	0.2%
327	1	0.2%
326	1	0.2%
325	1	0.2%
324	1	0.2%
Other values (473)	473	97.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.2%
2	1	0.2%
3	1	0.2%
4	1	0.2%
5	1	0.2%
6	1	0.2%
7	1	0.2%
8	1	0.2%
9	1	0.2%
10	1	0.2%

Value	Count	Frequency (%)
483	1	0.2%
482	1	0.2%
481	1	0.2%
480	1	0.2%
479	1	0.2%
478	1	0.2%
477	1	0.2%
476	1	0.2%
475	1	0.2%
474	1	0.2%

REGIÃO
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

SE	178
S	106
NE	100
CO	65
N	34

Length

Max length	2
Median length	2
Mean length	1.710144928
Min length	1

Characters and Unicode

Total characters	826
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CO
2nd row	CO
3rd row	NE
4th row	NE
5th row	CO

Common Values

Value	Count	Frequency (%)
SE	178	36.9%
S	106	21.9%
NE	100	20.7%
CO	65	13.5%
N	34	7.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
se	178	36.9%
s	106	21.9%
ne	100	20.7%
co	65	13.5%
n	34	7.0%

Most occurring characters

Value	Count	Frequency (%)
S	284	34.4%
E	278	33.7%
N	134	16.2%
C	65	7.9%
O	65	7.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	826	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	284	34.4%
E	278	33.7%
N	134	16.2%
C	65	7.9%
O	65	7.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	826	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	284	34.4%
E	278	33.7%
N	134	16.2%
C	65	7.9%
O	65	7.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	826	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
S	284	34.4%
E	278	33.7%
N	134	16.2%
C	65	7.9%
O	65	7.9%

UF
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	27
Distinct (%)	5.6%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

SP	85
MG	55
PR	36
SC	35
RS	35
Other values (22)	237

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	966
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.6%

Sample

1st row	GO
2nd row	GO
3rd row	CE
4th row	CE
5th row	GO

Common Values

Value	Count	Frequency (%)
SP	85	17.6%
MG	55	11.4%
PR	36	7.5%
SC	35	7.2%
RS	35	7.2%
PE	30	6.2%
MS	26	5.4%
RJ	26	5.4%
CE	23	4.8%
GO	21	4.3%
Other values (17)	111	23.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
sp	85	17.6%
mg	55	11.4%
pr	36	7.5%
sc	35	7.2%
rs	35	7.2%
pe	30	6.2%
rj	26	5.4%
ms	26	5.4%
ce	23	4.8%
go	21	4.3%
Other values (17)	111	23.0%

Most occurring characters

Value	Count	Frequency (%)
S	196	20.3%
P	179	18.5%
R	117	12.1%
M	107	11.1%
G	76	7.9%
E	68	7.0%
C	60	6.2%
A	39	4.0%
O	36	3.7%
J	26	2.7%
Other values (7)	62	6.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	966	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	196	20.3%
P	179	18.5%
R	117	12.1%
M	107	11.1%
G	76	7.9%
E	68	7.0%
C	60	6.2%
A	39	4.0%
O	36	3.7%
J	26	2.7%
Other values (7)	62	6.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	966	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	196	20.3%
P	179	18.5%
R	117	12.1%
M	107	11.1%
G	76	7.9%
E	68	7.0%
C	60	6.2%
A	39	4.0%
O	36	3.7%
J	26	2.7%
Other values (7)	62	6.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	966	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
S	196	20.3%
P	179	18.5%
R	117	12.1%
M	107	11.1%
G	76	7.9%
E	68	7.0%
C	60	6.2%
A	39	4.0%
O	36	3.7%
J	26	2.7%
Other values (7)	62	6.4%

ENTE
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	480
Distinct (%)	99.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

Rio Branco	2
Maracaju	2
Água Branca	2
Coxim	1
Águas Formosas	1
Other values (475)	475

Length

Max length	40
Median length	9
Mean length	11.10144928
Min length	3

Characters and Unicode

Total characters	5362
Distinct characters	62
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	477 ?
Unique (%)	98.8%

Sample

1st row	Abadia de Goiás
2nd row	Abadiânia
3rd row	Acarapé
4th row	Acopiara
5th row	Acreúna

Common Values

Value	Count	Frequency (%)
Rio Branco	2	0.4%
Maracaju	2	0.4%
Água Branca	2	0.4%
Coxim	1	0.2%
Águas Formosas	1	0.2%
Crato	1	0.2%
Bom Sucesso	1	0.2%
Marinópolis	1	0.2%
Tapera	1	0.2%
Taió	1	0.2%
Other values (470)	470	97.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
do	80	9.5%
governo	27	3.2%
estado	26	3.1%
de	24	2.9%
são	11	1.3%
rio	10	1.2%
sul	10	1.2%
nova	9	1.1%
da	9	1.1%
serra	7	0.8%
Other values (536)	629	74.7%

Most occurring characters

Value	Count	Frequency (%)
a	805	15.0%
o	485	9.0%
r	422	7.9%
	359	6.7%
i	334	6.2%
e	299	5.6%
d	243	4.5%
n	232	4.3%
s	195	3.6%
t	182	3.4%
Other values (52)	1806	33.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4269	79.6%
Uppercase Letter	725	13.5%
Space Separator	359	6.7%
Other Punctuation	5	0.1%
Dash Punctuation	4	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	805	18.9%
o	485	11.4%
r	422	9.9%
i	334	7.8%
e	299	7.0%
d	243	5.7%
n	232	5.4%
s	195	4.6%
t	182	4.3%
u	178	4.2%
Other values (26)	894	20.9%

Uppercase Letter

Value	Count	Frequency (%)
A	100	13.8%
C	74	10.2%
G	64	8.8%
S	59	8.1%
B	46	6.3%
M	43	5.9%
P	40	5.5%
E	38	5.2%
I	37	5.1%
T	35	4.8%
Other values (13)	189	26.1%

Space Separator

Value	Count	Frequency (%)
	359	100.0%

Other Punctuation

Value	Count	Frequency (%)
'	5	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4994	93.1%
Common	368	6.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	805	16.1%
o	485	9.7%
r	422	8.5%
i	334	6.7%
e	299	6.0%
d	243	4.9%
n	232	4.6%
s	195	3.9%
t	182	3.6%
u	178	3.6%
Other values (49)	1619	32.4%

Common

Value	Count	Frequency (%)
	359	97.6%
'	5	1.4%
-	4	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5155	96.1%
Latin 1 Sup	207	3.9%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	805	15.6%
o	485	9.4%
r	422	8.2%
	359	7.0%
i	334	6.5%
e	299	5.8%
d	243	4.7%
n	232	4.5%
s	195	3.8%
t	182	3.5%
Other values (40)	1599	31.0%

Latin 1 Sup

Value	Count	Frequency (%)
á	38	18.4%
ã	38	18.4%
í	28	13.5%
é	22	10.6%
ç	21	10.1%
ó	18	8.7%
Á	12	5.8%
â	10	4.8%
ú	8	3.9%
ô	6	2.9%
Other values (2)	6	2.9%

ANO
Date

Distinct	444
Distinct (%)	91.9%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

Minimum	1895-08-21 00:00:00
Maximum	2018-10-03 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

N.JUR
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.8%
Missing	10
Missing (%)	2.1%
Memory size	3.9 KiB

Autarquia	387
Órgão Adm. Direta	54
Fund. Dir. Púbico	22
Outros	10

Length

Max length	17
Median length	9
Mean length	10.22198732
Min length	6

Characters and Unicode

Total characters	4835
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Autarquia
2nd row	Autarquia
3rd row	Autarquia
4th row	Autarquia
5th row	Autarquia

Common Values

Value	Count	Frequency (%)
Autarquia	387	80.1%
Órgão Adm. Direta	54	11.2%
Fund. Dir. Púbico	22	4.6%
Outros	10	2.1%
(Missing)	10	2.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
autarquia	387	61.9%
órgão	54	8.6%
adm	54	8.6%
direta	54	8.6%
púbico	22	3.5%
dir	22	3.5%
fund	22	3.5%
outros	10	1.6%

Most occurring characters

Value	Count	Frequency (%)
a	828	17.1%
u	806	16.7%
r	527	10.9%
i	485	10.0%
t	451	9.3%
A	441	9.1%
q	387	8.0%
	152	3.1%
.	98	2.0%
o	86	1.8%
Other values (15)	574	11.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3960	81.9%
Uppercase Letter	625	12.9%
Space Separator	152	3.1%
Other Punctuation	98	2.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	828	20.9%
u	806	20.4%
r	527	13.3%
i	485	12.2%
t	451	11.4%
q	387	9.8%
o	86	2.2%
d	76	1.9%
g	54	1.4%
ã	54	1.4%
Other values (7)	206	5.2%

Uppercase Letter

Value	Count	Frequency (%)
A	441	70.6%
D	76	12.2%
Ó	54	8.6%
F	22	3.5%
P	22	3.5%
O	10	1.6%

Space Separator

Value	Count	Frequency (%)
	152	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	98	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4585	94.8%
Common	250	5.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	828	18.1%
u	806	17.6%
r	527	11.5%
i	485	10.6%
t	451	9.8%
A	441	9.6%
q	387	8.4%
o	86	1.9%
d	76	1.7%
D	76	1.7%
Other values (13)	422	9.2%

Common

Value	Count	Frequency (%)
	152	60.8%
.	98	39.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4705	97.3%
Latin 1 Sup	130	2.7%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	828	17.6%
u	806	17.1%
r	527	11.2%
i	485	10.3%
t	451	9.6%
A	441	9.4%
q	387	8.2%
	152	3.2%
.	98	2.1%
o	86	1.8%
Other values (12)	444	9.4%

Latin 1 Sup

Value	Count	Frequency (%)
Ó	54	41.5%
ã	54	41.5%
ú	22	16.9%

POP
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	453
Distinct (%)	99.3%
Missing	27
Missing (%)	5.6%
Infinite	0
Infinite (%)	0.0%
Mean	141151.5943

Minimum	1160
Maximum	2886698
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.9 KiB

Quantile statistics

Minimum	1160
5-th percentile	4695
Q1	16944.25
median	40056
Q3	125251.25
95-th percentile	592024
Maximum	2886698
Range	2885538
Interquartile range (IQR)	108307

Descriptive statistics

Standard deviation	302852.9044
Coefficient of variation (CV)	2.14558614
Kurtosis	35.46774161
Mean	141151.5943
Median Absolute Deviation (MAD)	30405.5
Skewness	5.277034408
Sum	64365127
Variance	9.171988168 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
413418	2	0.4%
48022	2	0.4%
17470	2	0.4%
18486	1	0.2%
43685	1	0.2%
517451	1	0.2%
45220	1	0.2%
58162	1	0.2%
22176	1	0.2%
68990	1	0.2%
Other values (443)	443	91.7%
(Missing)	27	5.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1160	1	0.2%
1799	1	0.2%
1818	1	0.2%
1865	1	0.2%
1983	1	0.2%
2106	1	0.2%
2251	1	0.2%
2284	1	0.2%
2509	1	0.2%
2840	1	0.2%

Value	Count	Frequency (%)
2886698	1	0.2%
2686612	1	0.2%
2219580	1	0.2%
1948626	1	0.2%
1653461	1	0.2%
1536097	1	0.2%
1488252	1	0.2%
1392121	1	0.2%
924624	1	0.2%
868075	1	0.2%

TAM.ATV
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	457
Distinct (%)	99.6%
Missing	24
Missing (%)	5.0%
Infinite	0
Infinite (%)	0.0%
Mean	279573311.6

Minimum	0
Maximum	5911148873
Zeros	2
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	3.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1732540.972
Q1	18593680.32
median	55063371.15
Q3	204031187.9
95-th percentile	1315184810
Maximum	5911148873
Range	5911148873
Interquartile range (IQR)	185437507.6

Descriptive statistics

Standard deviation	725646343.2
Coefficient of variation (CV)	2.595549407
Kurtosis	29.57138033
Mean	279573311.6
Median Absolute Deviation (MAD)	46430308.32
Skewness	5.095674096
Sum	1.2832415 × 10¹¹
Variance	5.265626154 × 10¹⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2	0.4%
76516506.48	2	0.4%
162942121.5	1	0.2%
566299010.4	1	0.2%
5451318911	1	0.2%
124476494.2	1	0.2%
555648134.4	1	0.2%
199447470.7	1	0.2%
93575.9	1	0.2%
46775387.98	1	0.2%
Other values (447)	447	92.5%
(Missing)	24	5.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	0.4%
17269.16	1	0.2%
21391.07	1	0.2%
43696.21	1	0.2%
45994.77	1	0.2%
93575.9	1	0.2%
97280.14	1	0.2%
146201.69	1	0.2%
174719.81	1	0.2%
247827.87	1	0.2%

Value	Count	Frequency (%)
5911148873	1	0.2%
5788725986	1	0.2%
5451318911	1	0.2%
4756271801	1	0.2%
4666187081	1	0.2%
4029788173	1	0.2%
3768034940	1	0.2%
3365482024	1	0.2%
2989411435	1	0.2%
2866506234	1	0.2%

AD.PROG
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

NÃO	282
SIM	199
SIM	2

Length

Max length	4
Median length	3
Mean length	3.004140787
Min length	3

Characters and Unicode

Total characters	1451
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NÃO
2nd row	NÃO
3rd row	NÃO
4th row	NÃO
5th row	NÃO

Common Values

Value	Count	Frequency (%)
NÃO	282	58.4%
SIM	199	41.2%
SIM	2	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
não	282	58.4%
sim	201	41.6%

Most occurring characters

Value	Count	Frequency (%)
N	282	19.4%
Ã	282	19.4%
O	282	19.4%
S	201	13.9%
I	201	13.9%
M	201	13.9%
	2	0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1449	99.9%
Space Separator	2	0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	282	19.5%
Ã	282	19.5%
O	282	19.5%
S	201	13.9%
I	201	13.9%
M	201	13.9%

Space Separator

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1449	99.9%
Common	2	0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	282	19.5%
Ã	282	19.5%
O	282	19.5%
S	201	13.9%
I	201	13.9%
M	201	13.9%

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1169	80.6%
Latin 1 Sup	282	19.4%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	282	24.1%
O	282	24.1%
S	201	17.2%
I	201	17.2%
M	201	17.2%
	2	0.2%

Latin 1 Sup

Value	Count	Frequency (%)
Ã	282	100.0%

C.PROG
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	7
Distinct (%)	3.5%
Missing	283
Missing (%)	58.6%
Memory size	3.9 KiB

NÃO	109
NÍVEL I	49
NÍVEL II	36
NÍVEL IV	2
NÍVEL III	2
Other values (2)	2

Length

Max length	9
Median length	3
Mean length	5.04
Min length	3

Characters and Unicode

Total characters	1008
Distinct characters	9
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	1.0%

Sample

1st row	NÃO
2nd row	NÃO
3rd row	NÃO
4th row	NÃO
5th row	NÃO

Common Values

Value	Count	Frequency (%)
NÃO	109	22.6%
NÍVEL I	49	10.1%
NÍVEL II	36	7.5%
NÍVEL IV	2	0.4%
NÍVEL III	2	0.4%
NIVEL II	1	0.2%
NÍVEL I	1	0.2%
(Missing)	283	58.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
não	109	37.5%
nível	90	30.9%
i	50	17.2%
ii	37	12.7%
iii	2	0.7%
iv	2	0.7%
nivel	1	0.3%

Most occurring characters

Value	Count	Frequency (%)
N	200	19.8%
I	133	13.2%
Ã	109	10.8%
O	109	10.8%
V	93	9.2%
	92	9.1%
E	91	9.0%
L	91	9.0%
Í	90	8.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	916	90.9%
Space Separator	92	9.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	200	21.8%
I	133	14.5%
Ã	109	11.9%
O	109	11.9%
V	93	10.2%
E	91	9.9%
L	91	9.9%
Í	90	9.8%

Space Separator

Value	Count	Frequency (%)
	92	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	916	90.9%
Common	92	9.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	200	21.8%
I	133	14.5%
Ã	109	11.9%
O	109	11.9%
V	93	10.2%
E	91	9.9%
L	91	9.9%
Í	90	9.8%

Common

Value	Count	Frequency (%)
	92	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	809	80.3%
Latin 1 Sup	199	19.7%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	200	24.7%
I	133	16.4%
O	109	13.5%
V	93	11.5%
	92	11.4%
E	91	11.2%
L	91	11.2%

Latin 1 Sup

Value	Count	Frequency (%)
Ã	109	54.8%
Í	90	45.2%

PRT_massa
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

MÉDIO PORTE	280
PEQUENO PORTE	105
GRANDE PORTE	70
ESTADO/DF	27
NÃO CLASSIFICADO	1

Length

Max length	16
Median length	11
Mean length	11.47826087
Min length	9

Characters and Unicode

Total characters	5544
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.2%

Sample

1st row	PEQUENO PORTE
2nd row	PEQUENO PORTE
3rd row	PEQUENO PORTE
4th row	MÉDIO PORTE
5th row	MÉDIO PORTE

Common Values

Value	Count	Frequency (%)
MÉDIO PORTE	280	58.0%
PEQUENO PORTE	105	21.7%
GRANDE PORTE	70	14.5%
ESTADO/DF	27	5.6%
NÃO CLASSIFICADO	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
porte	455	48.5%
médio	280	29.8%
pequeno	105	11.2%
grande	70	7.5%
estado/df	27	2.9%
classificado	1	0.1%
não	1	0.1%

Most occurring characters

Value	Count	Frequency (%)
O	869	15.7%
E	762	13.7%
P	560	10.1%
R	525	9.5%
T	482	8.7%
	456	8.2%
D	405	7.3%
I	282	5.1%
M	280	5.1%
É	280	5.1%
Other values (11)	643	11.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	5061	91.3%
Space Separator	456	8.2%
Other Punctuation	27	0.5%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
O	869	17.2%
E	762	15.1%
P	560	11.1%
R	525	10.4%
T	482	9.5%
D	405	8.0%
I	282	5.6%
M	280	5.5%
É	280	5.5%
N	176	3.5%
Other values (9)	440	8.7%

Space Separator

Value	Count	Frequency (%)
	456	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	27	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5061	91.3%
Common	483	8.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
O	869	17.2%
E	762	15.1%
P	560	11.1%
R	525	10.4%
T	482	9.5%
D	405	8.0%
I	282	5.6%
M	280	5.5%
É	280	5.5%
N	176	3.5%
Other values (9)	440	8.7%

Common

Value	Count	Frequency (%)
	456	94.4%
/	27	5.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5263	94.9%
Latin 1 Sup	281	5.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
O	869	16.5%
E	762	14.5%
P	560	10.6%
R	525	10.0%
T	482	9.2%
	456	8.7%
D	405	7.7%
I	282	5.4%
M	280	5.3%
N	176	3.3%
Other values (9)	466	8.9%

Latin 1 Sup

Value	Count	Frequency (%)
É	280	99.6%
Ã	1	0.4%

MassaSeg.
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

mais favorável	241
menos favorável	214
ESTADO/DF	27
NÃO CLASSIFICADO	1

Length

Max length	16
Median length	14
Mean length	14.16770186
Min length	9

Characters and Unicode

Total characters	6843
Distinct characters	26
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.2%

Sample

1st row	mais favorável
2nd row	mais favorável
3rd row	mais favorável
4th row	mais favorável
5th row	menos favorável

Common Values

Value	Count	Frequency (%)
mais favorável	241	49.9%
menos favorável	214	44.3%
ESTADO/DF	27	5.6%
NÃO CLASSIFICADO	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
favorável	455	48.5%
mais	241	25.7%
menos	214	22.8%
estado/df	27	2.9%
classificado	1	0.1%
não	1	0.1%

Most occurring characters

Value	Count	Frequency (%)
v	910	13.3%
a	696	10.2%
o	669	9.8%
e	669	9.8%
	456	6.7%
m	455	6.6%
s	455	6.6%
f	455	6.6%
r	455	6.6%
á	455	6.6%
Other values (16)	1168	17.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6129	89.6%
Space Separator	456	6.7%
Uppercase Letter	231	3.4%
Other Punctuation	27	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
v	910	14.8%
a	696	11.4%
o	669	10.9%
e	669	10.9%
m	455	7.4%
s	455	7.4%
f	455	7.4%
r	455	7.4%
á	455	7.4%
l	455	7.4%
Other values (2)	455	7.4%

Uppercase Letter

Value	Count	Frequency (%)
D	55	23.8%
S	29	12.6%
A	29	12.6%
O	29	12.6%
F	28	12.1%
E	27	11.7%
T	27	11.7%
C	2	0.9%
I	2	0.9%
N	1	0.4%
Other values (2)	2	0.9%

Space Separator

Value	Count	Frequency (%)
	456	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	27	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6360	92.9%
Common	483	7.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
v	910	14.3%
a	696	10.9%
o	669	10.5%
e	669	10.5%
m	455	7.2%
s	455	7.2%
f	455	7.2%
r	455	7.2%
á	455	7.2%
l	455	7.2%
Other values (14)	686	10.8%

Common

Value	Count	Frequency (%)
	456	94.4%
/	27	5.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6387	93.3%
Latin 1 Sup	456	6.7%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
v	910	14.2%
a	696	10.9%
o	669	10.5%
e	669	10.5%
	456	7.1%
m	455	7.1%
s	455	7.1%
f	455	7.1%
r	455	7.1%
l	455	7.1%
Other values (14)	712	11.1%

Latin 1 Sup

Value	Count	Frequency (%)
á	455	99.8%
Ã	1	0.2%

GR_POD
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

1	483

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	483	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	483	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	483	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	483	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	483	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	483	100.0%

GR_SEGR
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

1.0	399
0.0	83

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	399	82.6%
0.0	83	17.2%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	399	82.8%
0.0	83	17.2%

Most occurring characters

Value	Count	Frequency (%)
0	565	39.1%
.	482	33.3%
1	399	27.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	964	66.7%
Other Punctuation	482	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	565	58.6%
1	399	41.4%

Other Punctuation

Value	Count	Frequency (%)
.	482	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1446	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	565	39.1%
.	482	33.3%
1	399	27.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	565	39.1%
.	482	33.3%
1	399	27.6%

GR_C.ÉT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	3
Missing (%)	0.6%
Memory size	3.9 KiB

0.0	337
1.0	143

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1440
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	337	69.8%
1.0	143	29.6%
(Missing)	3	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	337	70.2%
1.0	143	29.8%

Most occurring characters

Value	Count	Frequency (%)
0	817	56.7%
.	480	33.3%
1	143	9.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	960	66.7%
Other Punctuation	480	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	817	85.1%
1	143	14.9%

Other Punctuation

Value	Count	Frequency (%)
.	480	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1440	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	817	56.7%
.	480	33.3%
1	143	9.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1440	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	817	56.7%
.	480	33.3%
1	143	9.9%

CIE_REL
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

0	316
1	167

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	316	65.4%
1	167	34.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	316	65.4%
1	167	34.6%

Most occurring characters

Value	Count	Frequency (%)
0	316	65.4%
1	167	34.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	316	65.4%
1	167	34.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	316	65.4%
1	167	34.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	316	65.4%
1	167	34.6%

CIE_FISC
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	4
Missing (%)	0.8%
Memory size	3.9 KiB

REG	445
JUD	22
IRG	12

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1437
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	REG
2nd row	REG
3rd row	REG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	445	92.1%
JUD	22	4.6%
IRG	12	2.5%
(Missing)	4	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	445	92.9%
jud	22	4.6%
irg	12	2.5%

Most occurring characters

Value	Count	Frequency (%)
R	457	31.8%
G	457	31.8%
E	445	31.0%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	12	0.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1437	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	457	31.8%
G	457	31.8%
E	445	31.0%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	12	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1437	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	457	31.8%
G	457	31.8%
E	445	31.0%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	12	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1437	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	457	31.8%
G	457	31.8%
E	445	31.0%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	12	0.8%

CIE_AUD
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

REG	474
JUD	5
IRG	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1449
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	REG
2nd row	REG
3rd row	REG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	474	98.1%
JUD	5	1.0%
IRG	4	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	474	98.1%
jud	5	1.0%
irg	4	0.8%

Most occurring characters

Value	Count	Frequency (%)
R	478	33.0%
G	478	33.0%
E	474	32.7%
J	5	0.3%
U	5	0.3%
D	5	0.3%
I	4	0.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1449	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	478	33.0%
G	478	33.0%
E	474	32.7%
J	5	0.3%
U	5	0.3%
D	5	0.3%
I	4	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1449	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	478	33.0%
G	478	33.0%
E	474	32.7%
J	5	0.3%
U	5	0.3%
D	5	0.3%
I	4	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1449	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	478	33.0%
G	478	33.0%
E	474	32.7%
J	5	0.3%
U	5	0.3%
D	5	0.3%
I	4	0.3%

CIE_CRP
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

REG	251
JUD	149
IRG	82

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	IRG
2nd row	JUD
3rd row	IRG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	251	52.0%
JUD	149	30.8%
IRG	82	17.0%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	251	52.1%
jud	149	30.9%
irg	82	17.0%

Most occurring characters

Value	Count	Frequency (%)
R	333	23.0%
G	333	23.0%
E	251	17.4%
J	149	10.3%
U	149	10.3%
D	149	10.3%
I	82	5.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1446	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	333	23.0%
G	333	23.0%
E	251	17.4%
J	149	10.3%
U	149	10.3%
D	149	10.3%
I	82	5.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1446	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	333	23.0%
G	333	23.0%
E	251	17.4%
J	149	10.3%
U	149	10.3%
D	149	10.3%
I	82	5.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	333	23.0%
G	333	23.0%
E	251	17.4%
J	149	10.3%
U	149	10.3%
D	149	10.3%
I	82	5.7%

GI_DIV.CART
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

REG	447
JUD	22
IRG	13

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	REG
2nd row	REG
3rd row	REG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	447	92.5%
JUD	22	4.6%
IRG	13	2.7%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	447	92.7%
jud	22	4.6%
irg	13	2.7%

Most occurring characters

Value	Count	Frequency (%)
R	460	31.8%
G	460	31.8%
E	447	30.9%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	13	0.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1446	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	460	31.8%
G	460	31.8%
E	447	30.9%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	13	0.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1446	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	460	31.8%
G	460	31.8%
E	447	30.9%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	13	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	460	31.8%
G	460	31.8%
E	447	30.9%
J	22	1.5%
U	22	1.5%
D	22	1.5%
I	13	0.9%

GI_C.TÉC
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	3
Missing (%)	0.6%
Memory size	3.9 KiB

B	332
C	90
A	58

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	480
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	B
2nd row	C
3rd row	C
4th row	B
5th row	B

Common Values

Value	Count	Frequency (%)
B	332	68.7%
C	90	18.6%
A	58	12.0%
(Missing)	3	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
b	332	69.2%
c	90	18.8%
a	58	12.1%

Most occurring characters

Value	Count	Frequency (%)
B	332	69.2%
C	90	18.8%
A	58	12.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	480	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
B	332	69.2%
C	90	18.8%
A	58	12.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	480	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
B	332	69.2%
C	90	18.8%
A	58	12.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	480	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
B	332	69.2%
C	90	18.8%
A	58	12.1%

GI_P.INV
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

1	446
0	37

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	446	92.3%
0	37	7.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	446	92.3%
0	37	7.7%

Most occurring characters

Value	Count	Frequency (%)
1	446	92.3%
0	37	7.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	446	92.3%
0	37	7.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	446	92.3%
0	37	7.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	446	92.3%
0	37	7.7%

GI_COMITÊ
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

1	412
0	71

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	412	85.3%
0	71	14.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	412	85.3%
0	71	14.7%

Most occurring characters

Value	Count	Frequency (%)
1	412	85.3%
0	71	14.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	412	85.3%
0	71	14.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	412	85.3%
0	71	14.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	412	85.3%
0	71	14.7%

GI_CONS
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.4%
Missing	12
Missing (%)	2.5%
Memory size	3.9 KiB

1.0	297
0.0	174

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1413
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	297	61.5%
0.0	174	36.0%
(Missing)	12	2.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	297	63.1%
0.0	174	36.9%

Most occurring characters

Value	Count	Frequency (%)
0	645	45.6%
.	471	33.3%
1	297	21.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	942	66.7%
Other Punctuation	471	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	645	68.5%
1	297	31.5%

Other Punctuation

Value	Count	Frequency (%)
.	471	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1413	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	645	45.6%
.	471	33.3%
1	297	21.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1413	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	645	45.6%
.	471	33.3%
1	297	21.0%

SA_AMRTZ
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

0	327
1	156

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	327	67.7%
1	156	32.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	327	67.7%
1	156	32.3%

Most occurring characters

Value	Count	Frequency (%)
0	327	67.7%
1	156	32.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	327	67.7%
1	156	32.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	327	67.7%
1	156	32.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	327	67.7%
1	156	32.3%

SA_PUB.REL
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

REG	316
JUD	95
IRG	72

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1449
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	IRG
2nd row	JUD
3rd row	REG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	316	65.4%
JUD	95	19.7%
IRG	72	14.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	316	65.4%
jud	95	19.7%
irg	72	14.9%

Most occurring characters

Value	Count	Frequency (%)
R	388	26.8%
G	388	26.8%
E	316	21.8%
J	95	6.6%
U	95	6.6%
D	95	6.6%
I	72	5.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1449	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	388	26.8%
G	388	26.8%
E	316	21.8%
J	95	6.6%
U	95	6.6%
D	95	6.6%
I	72	5.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1449	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	388	26.8%
G	388	26.8%
E	316	21.8%
J	95	6.6%
U	95	6.6%
D	95	6.6%
I	72	5.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1449	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	388	26.8%
G	388	26.8%
E	316	21.8%
J	95	6.6%
U	95	6.6%
D	95	6.6%
I	72	5.0%

SA_REPAS
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	0.6%
Missing	5
Missing (%)	1.0%
Memory size	3.9 KiB

REG	391
JUD	57
IRG	30

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1434
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	REG
2nd row	REG
3rd row	IRG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	391	81.0%
JUD	57	11.8%
IRG	30	6.2%
(Missing)	5	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	391	81.8%
jud	57	11.9%
irg	30	6.3%

Most occurring characters

Value	Count	Frequency (%)
R	421	29.4%
G	421	29.4%
E	391	27.3%
J	57	4.0%
U	57	4.0%
D	57	4.0%
I	30	2.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1434	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	421	29.4%
G	421	29.4%
E	391	27.3%
J	57	4.0%
U	57	4.0%
D	57	4.0%
I	30	2.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1434	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	421	29.4%
G	421	29.4%
E	391	27.3%
J	57	4.0%
U	57	4.0%
D	57	4.0%
I	30	2.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1434	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	421	29.4%
G	421	29.4%
E	391	27.3%
J	57	4.0%
U	57	4.0%
D	57	4.0%
I	30	2.1%

SA_R.ALIQ
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

0.0	252
1.0	230

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	252	52.2%
1.0	230	47.6%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	252	52.3%
1.0	230	47.7%

Most occurring characters

Value	Count	Frequency (%)
0	734	50.8%
.	482	33.3%
1	230	15.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	964	66.7%
Other Punctuation	482	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	734	76.1%
1	230	23.9%

Other Punctuation

Value	Count	Frequency (%)
.	482	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1446	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	734	50.8%
.	482	33.3%
1	230	15.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	734	50.8%
.	482	33.3%
1	230	15.9%

GTI_POL.INFR.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

0	368
1	115

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	368	76.2%
1	115	23.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	368	76.2%
1	115	23.8%

Most occurring characters

Value	Count	Frequency (%)
0	368	76.2%
1	115	23.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	368	76.2%
1	115	23.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	368	76.2%
1	115	23.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	368	76.2%
1	115	23.8%

GTI_INV.TI
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

1.0	248
0.0	234

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	248	51.3%
0.0	234	48.4%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	248	51.5%
0.0	234	48.5%

Most occurring characters

Value	Count	Frequency (%)
0	716	49.5%
.	482	33.3%
1	248	17.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	964	66.7%
Other Punctuation	482	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	716	74.3%
1	248	25.7%

Other Punctuation

Value	Count	Frequency (%)
.	482	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1446	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	716	49.5%
.	482	33.3%
1	248	17.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	716	49.5%
.	482	33.3%
1	248	17.2%

DDM_CART
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	3
Missing (%)	0.6%
Memory size	3.9 KiB

1.0	425
0.0	55

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1440
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	425	88.0%
0.0	55	11.4%
(Missing)	3	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	425	88.5%
0.0	55	11.5%

Most occurring characters

Value	Count	Frequency (%)
0	535	37.2%
.	480	33.3%
1	425	29.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	960	66.7%
Other Punctuation	480	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	535	55.7%
1	425	44.3%

Other Punctuation

Value	Count	Frequency (%)
.	480	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1440	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	535	37.2%
.	480	33.3%
1	425	29.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1440	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	535	37.2%
.	480	33.3%
1	425	29.5%

DDM_ACES
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	2
Missing (%)	0.4%
Memory size	3.9 KiB

REG	480
JUD	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1443
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.2%

Sample

1st row	REG
2nd row	REG
3rd row	REG
4th row	REG
5th row	REG

Common Values

Value	Count	Frequency (%)
REG	480	99.4%
JUD	1	0.2%
(Missing)	2	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
reg	480	99.8%
jud	1	0.2%

Most occurring characters

Value	Count	Frequency (%)
R	480	33.3%
E	480	33.3%
G	480	33.3%
J	1	0.1%
U	1	0.1%
D	1	0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1443	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	480	33.3%
E	480	33.3%
G	480	33.3%
J	1	0.1%
U	1	0.1%
D	1	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1443	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	480	33.3%
E	480	33.3%
G	480	33.3%
J	1	0.1%
U	1	0.1%
D	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1443	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
R	480	33.3%
E	480	33.3%
G	480	33.3%
J	1	0.1%
U	1	0.1%
D	1	0.1%

DDM_ATAS
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.4%
Missing	5
Missing (%)	1.0%
Memory size	3.9 KiB

1.0	324
0.0	154

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1434
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	324	67.1%
0.0	154	31.9%
(Missing)	5	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	324	67.8%
0.0	154	32.2%

Most occurring characters

Value	Count	Frequency (%)
0	632	44.1%
.	478	33.3%
1	324	22.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	956	66.7%
Other Punctuation	478	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	632	66.1%
1	324	33.9%

Other Punctuation

Value	Count	Frequency (%)
.	478	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1434	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	632	44.1%
.	478	33.3%
1	324	22.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1434	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	632	44.1%
.	478	33.3%
1	324	22.6%

RP_REG.ENV
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.6%
Missing	3
Missing (%)	0.6%
Memory size	3.9 KiB

A	202
B	181
C	97

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	480
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A
2nd row	B
3rd row	B
4th row	A
5th row	A

Common Values

Value	Count	Frequency (%)
A	202	41.8%
B	181	37.5%
C	97	20.1%
(Missing)	3	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	202	42.1%
b	181	37.7%
c	97	20.2%

Most occurring characters

Value	Count	Frequency (%)
A	202	42.1%
B	181	37.7%
C	97	20.2%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	480	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	202	42.1%
B	181	37.7%
C	97	20.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	480	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	202	42.1%
B	181	37.7%
C	97	20.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	480	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	202	42.1%
B	181	37.7%
C	97	20.2%

RP_REL.GOV
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.4%
Missing	5
Missing (%)	1.0%
Memory size	3.9 KiB

0.0	331
1.0	147

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1434
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	331	68.5%
1.0	147	30.4%
(Missing)	5	1.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	331	69.2%
1.0	147	30.8%

Most occurring characters

Value	Count	Frequency (%)
0	809	56.4%
.	478	33.3%
1	147	10.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	956	66.7%
Other Punctuation	478	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	809	84.6%
1	147	15.4%

Other Punctuation

Value	Count	Frequency (%)
.	478	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1434	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	809	56.4%
.	478	33.3%
1	147	10.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1434	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	809	56.4%
.	478	33.3%
1	147	10.3%

RP_SITE
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

1.0	419
0.0	63

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	419	86.7%
0.0	63	13.0%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	419	86.9%
0.0	63	13.1%

Most occurring characters

Value	Count	Frequency (%)
0	545	37.7%
.	482	33.3%
1	419	29.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	964	66.7%
Other Punctuation	482	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	545	56.5%
1	419	43.5%

Other Punctuation

Value	Count	Frequency (%)
.	482	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1446	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	545	37.7%
.	482	33.3%
1	419	29.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	545	37.7%
.	482	33.3%
1	419	29.0%

PS_OUV
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	4
Missing (%)	0.8%
Memory size	3.9 KiB

1.0	403
0.0	76

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1437
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	403	83.4%
0.0	76	15.7%
(Missing)	4	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	403	84.1%
0.0	76	15.9%

Most occurring characters

Value	Count	Frequency (%)
0	555	38.6%
.	479	33.3%
1	403	28.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	958	66.7%
Other Punctuation	479	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	555	57.9%
1	403	42.1%

Other Punctuation

Value	Count	Frequency (%)
.	479	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1437	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	555	38.6%
.	479	33.3%
1	403	28.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1437	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	555	38.6%
.	479	33.3%
1	403	28.0%

PS_GEST
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

0.0	376
1.0	106

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	376	77.8%
1.0	106	21.9%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	376	78.0%
1.0	106	22.0%

Most occurring characters

Value	Count	Frequency (%)
0	858	59.3%
.	482	33.3%
1	106	7.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	964	66.7%
Other Punctuation	482	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	858	89.0%
1	106	11.0%

Other Punctuation

Value	Count	Frequency (%)
.	482	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1446	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	858	59.3%
.	482	33.3%
1	106	7.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	858	59.3%
.	482	33.3%
1	106	7.3%

IP_REP.CF
Categorical

HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	0.6%
Missing	16
Missing (%)	3.3%
Memory size	3.9 KiB

A	185
B	178
C	104

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	467
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	B
2nd row	C
3rd row	B
4th row	A
5th row	A

Common Values

Value	Count	Frequency (%)
A	185	38.3%
B	178	36.9%
C	104	21.5%
(Missing)	16	3.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	185	39.6%
b	178	38.1%
c	104	22.3%

Most occurring characters

Value	Count	Frequency (%)
A	185	39.6%
B	178	38.1%
C	104	22.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	467	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	185	39.6%
B	178	38.1%
C	104	22.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	467	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	185	39.6%
B	178	38.1%
C	104	22.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	467	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	185	39.6%
B	178	38.1%
C	104	22.3%

IP_SELEC
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	2
Missing (%)	0.4%
Memory size	3.9 KiB

ESC	381
EL	100

Length

Max length	3
Median length	3
Mean length	2.792099792
Min length	2

Characters and Unicode

Total characters	1343
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	EL
2nd row	EL
3rd row	ESC
4th row	ESC
5th row	EL

Common Values

Value	Count	Frequency (%)
ESC	381	78.9%
EL	100	20.7%
(Missing)	2	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
esc	381	79.2%
el	100	20.8%

Most occurring characters

Value	Count	Frequency (%)
E	481	35.8%
S	381	28.4%
C	381	28.4%
L	100	7.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1343	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
E	481	35.8%
S	381	28.4%
C	381	28.4%
L	100	7.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1343	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
E	481	35.8%
S	381	28.4%
C	381	28.4%
L	100	7.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1343	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
E	481	35.8%
S	381	28.4%
C	381	28.4%
L	100	7.4%

LI_CERT.MB
Categorical

HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	0.6%
Missing	16
Missing (%)	3.3%
Memory size	3.9 KiB

C	326
B	123
A	18

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	467
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	C
2nd row	C
3rd row	C
4th row	C
5th row	C

Common Values

Value	Count	Frequency (%)
C	326	67.5%
B	123	25.5%
A	18	3.7%
(Missing)	16	3.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
c	326	69.8%
b	123	26.3%
a	18	3.9%

Most occurring characters

Value	Count	Frequency (%)
C	326	69.8%
B	123	26.3%
A	18	3.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	467	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
C	326	69.8%
B	123	26.3%
A	18	3.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	467	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
C	326	69.8%
B	123	26.3%
A	18	3.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	467	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
C	326	69.8%
B	123	26.3%
A	18	3.9%

LI_DIR.CERT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	3.9 KiB

1	375
0	108

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	483
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	375	77.6%
0	108	22.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	375	77.6%
0	108	22.4%

Most occurring characters

Value	Count	Frequency (%)
1	375	77.6%
0	108	22.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	483	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	375	77.6%
0	108	22.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	483	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	375	77.6%
0	108	22.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	483	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	375	77.6%
0	108	22.4%

LI_P.EST.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.4%
Missing	1
Missing (%)	0.2%
Memory size	3.9 KiB

0.0	340
1.0	142

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	340	70.4%
1.0	142	29.4%
(Missing)	1	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	340	70.5%
1.0	142	29.5%

Most occurring characters

Value	Count	Frequency (%)
0	822	56.8%
.	482	33.3%
1	142	9.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	964	66.7%
Other Punctuation	482	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	822	85.3%
1	142	14.7%

Other Punctuation

Value	Count	Frequency (%)
.	482	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1446	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	822	56.8%
.	482	33.3%
1	142	9.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	822	56.8%
.	482	33.3%
1	142	9.8%

R.FIN
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	450
Distinct (%)	99.3%
Missing	30
Missing (%)	6.2%
Infinite	0
Infinite (%)	0.0%
Mean	-163181126.2

Minimum	-1.701491796 × 10¹⁰
Maximum	875482695.9
Zeros	0
Zeros (%)	0.0%
Negative	175
Negative (%)	36.2%
Memory size	3.9 KiB

Quantile statistics

Minimum	-1.701491796 × 10¹⁰
5-th percentile	-323537271.8
Q1	-2666727.3
median	1544334.33
Q3	11258936.5
95-th percentile	63448488.4
Maximum	875482695.9
Range	1.789040066 × 10¹⁰
Interquartile range (IQR)	13925663.8

Descriptive statistics

Standard deviation	1227011676
Coefficient of variation (CV)	-7.519323496
Kurtosis	115.208654
Mean	-163181126.2
Median Absolute Deviation (MAD)	6061261.38
Skewness	-10.13106641
Sum	-7.392105017 × 10¹⁰
Variance	1.505557654 × 10¹⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-354697.62	2	0.4%
91572003.13	2	0.4%
2829015.75	2	0.4%
-13828676.05	1	0.2%
630624480.8	1	0.2%
62314.4	1	0.2%
-4937919.22	1	0.2%
1319148.91	1	0.2%
-2383647.09	1	0.2%
110623841	1	0.2%
Other values (440)	440	91.1%
(Missing)	30	6.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1.701491796 × 10¹⁰	1	0.2%
-1.255354433 × 10¹⁰	1	0.2%
-1.041227888 × 10¹⁰	1	0.2%
-7885884880	1	0.2%
-4741300986	1	0.2%
-3332981446	1	0.2%
-3129537815	1	0.2%
-2986135221	1	0.2%
-2429500958	1	0.2%
-2017776073	1	0.2%

Value	Count	Frequency (%)
875482695.9	1	0.2%
630624480.8	1	0.2%
452718416.6	1	0.2%
248984384.6	1	0.2%
207698621.2	1	0.2%
196211453	1	0.2%
125347268.8	1	0.2%
122063433.7	1	0.2%
110623841	1	0.2%
99548187.13	1	0.2%

IND.SF
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	446
Distinct (%)	98.2%
Missing	29
Missing (%)	6.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.80716749

Minimum	-1.093554999 × 10^-16
Maximum	29.70066657
Zeros	6
Zeros (%)	1.2%
Negative	1
Negative (%)	0.2%
Memory size	3.9 KiB

Quantile statistics

Minimum	-1.093554999 × 10^-16
5-th percentile	0.4012543475
Q1	0.8014003234
median	1.247655843
Q3	2.191206375
95-th percentile	4.459868052
Maximum	29.70066657
Range	29.70066657
Interquartile range (IQR)	1.389806051

Descriptive statistics

Standard deviation	2.016202241
Coefficient of variation (CV)	1.115669827
Kurtosis	83.49025254
Mean	1.80716749
Median Absolute Deviation (MAD)	0.5728141392
Skewness	7.006730694
Sum	820.4540404
Variance	4.065071475
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6	1.2%
1.214839343	2	0.4%
3.228919572	2	0.4%
0.8720105457	2	0.4%
1.300127499	1	0.2%
2.766044152	1	0.2%
1.593739534	1	0.2%
0.7724198639	1	0.2%
1.011823406	1	0.2%
1.664840115	1	0.2%
Other values (436)	436	90.3%
(Missing)	29	6.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1.093554999 × 10^-16	1	0.2%
0	6	1.2%
0.1089666289	1	0.2%
0.1595588626	1	0.2%
0.1620960833	1	0.2%
0.2036174322	1	0.2%
0.242773749	1	0.2%
0.2476586728	1	0.2%
0.2565822121	1	0.2%
0.2949754814	1	0.2%

Value	Count	Frequency (%)
29.70066657	1	0.2%
11.45502949	1	0.2%
10.93246383	1	0.2%
10.81913327	1	0.2%
9.763892328	1	0.2%
8.922669032	1	0.2%
7.264401404	1	0.2%
6.718568449	1	0.2%
6.608458561	1	0.2%
6.540222056	1	0.2%

R.INV
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	457
Distinct (%)	99.3%
Missing	23
Missing (%)	4.8%
Infinite	0
Infinite (%)	0.0%
Mean	37604066.64

Minimum	-2151664669
Maximum	1220762395
Zeros	1
Zeros (%)	0.2%
Negative	52
Negative (%)	10.8%
Memory size	3.9 KiB

Quantile statistics

Minimum	-2151664669
5-th percentile	-2135781.922
Q1	2230268.38
median	7858158.695
Q3	31813110.21
95-th percentile	178624675.9
Maximum	1220762395
Range	3372427063
Interquartile range (IQR)	29582841.83

Descriptive statistics

Standard deviation	158581892
Coefficient of variation (CV)	4.217147402
Kurtosis	91.05744841
Mean	37604066.64
Median Absolute Deviation (MAD)	7804801.745
Skewness	-3.400565898
Sum	1.729787066 × 10¹⁰
Variance	2.514821646 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
90215306.37	2	0.4%
-339686.38	2	0.4%
9808592.09	2	0.4%
5066195.28	1	0.2%
6655564.67	1	0.2%
11206110.6	1	0.2%
-2801179.48	1	0.2%
-2236857.72	1	0.2%
60727201.9	1	0.2%
949190223	1	0.2%
Other values (447)	447	92.5%
(Missing)	23	4.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2151664669	1	0.2%
-431129345.9	1	0.2%
-265616622	1	0.2%
-48203871.34	1	0.2%
-42856336.28	1	0.2%
-26744651.09	1	0.2%
-22574067.49	1	0.2%
-14659401.15	1	0.2%
-11735045.93	1	0.2%
-11095125.22	1	0.2%

Value	Count	Frequency (%)
1220762395	1	0.2%
949190223	1	0.2%
845141645.1	1	0.2%
824575279.5	1	0.2%
623691267.1	1	0.2%
618817308.9	1	0.2%
551628734.7	1	0.2%
490763935	1	0.2%
464028616.7	1	0.2%
424901190.8	1	0.2%

VAR.INV
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	456
Distinct (%)	99.3%
Missing	24
Missing (%)	5.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3174280104

Minimum	-0.99701821
Maximum	13.62771481
Zeros	0
Zeros (%)	0.0%
Negative	52
Negative (%)	10.8%
Memory size	3.9 KiB

Quantile statistics

Minimum	-0.99701821
5-th percentile	-0.1757282473
Q1	0.1169265351
median	0.1844074437
Q3	0.2454681355
95-th percentile	0.6262406429
Maximum	13.62771481
Range	14.62473302
Interquartile range (IQR)	0.1285416004

Descriptive statistics

Standard deviation	1.14964428
Coefficient of variation (CV)	3.621748056
Kurtosis	78.55715147
Mean	0.3174280104
Median Absolute Deviation (MAD)	0.06535249045
Skewness	8.338313836
Sum	145.6994568
Variance	1.321681969
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.2308910325	2	0.4%
-0.06280884732	2	0.4%
0.1470379067	2	0.4%
0.1232589633	1	0.2%
0.1861183763	1	0.2%
0.1979928544	1	0.2%
0.01726719009	1	0.2%
0.1316443366	1	0.2%
0.7229333871	1	0.2%
0.2251705964	1	0.2%
Other values (446)	446	92.3%
(Missing)	24	5.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.99701821	1	0.2%
-0.9496865031	1	0.2%
-0.7806316718	1	0.2%
-0.780507833	1	0.2%
-0.7256682355	1	0.2%
-0.6458549494	1	0.2%
-0.6095271057	1	0.2%
-0.5924152702	1	0.2%
-0.5786307045	1	0.2%
-0.5649803351	1	0.2%

Value	Count	Frequency (%)
13.62771481	1	0.2%
11.8941088	1	0.2%
10.03296768	1	0.2%
7.505295387	1	0.2%
6.829631084	1	0.2%
6.403864992	1	0.2%
4.106976221	1	0.2%
3.113127511	1	0.2%
2.375138446	1	0.2%
1.720728111	1	0.2%

R.AT
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	411
Distinct (%)	99.5%
Missing	70
Missing (%)	14.5%
Infinite	0
Infinite (%)	0.0%
Mean	-4921375352

Minimum	-3.470908443 × 10¹¹
Maximum	38495499.24
Zeros	0
Zeros (%)	0.0%
Negative	406
Negative (%)	84.1%
Memory size	3.9 KiB

Quantile statistics

Minimum	-3.470908443 × 10¹¹
5-th percentile	-1.274789586 × 10¹⁰
Q1	-586788614.3
median	-139066840.8
Q3	-48998953.69
95-th percentile	-11444562.98
Maximum	38495499.24
Range	3.471293398 × 10¹¹
Interquartile range (IQR)	537789660.6

Descriptive statistics

Standard deviation	2.804579137 × 10¹⁰
Coefficient of variation (CV)	-5.698771048
Kurtosis	91.6647327
Mean	-4921375352
Median Absolute Deviation (MAD)	111029049
Skewness	-9.071377212
Sum	-2.03252802 × 10¹²
Variance	7.865664135 × 10²⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-295511611.2	2	0.4%
-36341130.14	2	0.4%
-7.683254905 × 10¹⁰	1	0.2%
-993867365.9	1	0.2%
-16076887.45	1	0.2%
-1.312349732 × 10¹⁰	1	0.2%
-1674530866	1	0.2%
-72459138.78	1	0.2%
-46424138.9	1	0.2%
-1036952299	1	0.2%
Other values (401)	401	83.0%
(Missing)	70	14.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-3.470908443 × 10¹¹	1	0.2%
-2.749190753 × 10¹¹	1	0.2%
-2.570615879 × 10¹¹	1	0.2%
-1.462154403 × 10¹¹	1	0.2%
-1.198480442 × 10¹¹	1	0.2%
-1.010404685 × 10¹¹	1	0.2%
-7.683254905 × 10¹⁰	1	0.2%
-6.725115857 × 10¹⁰	1	0.2%
-6.491523952 × 10¹⁰	1	0.2%
-5.190426728 × 10¹⁰	1	0.2%

Value	Count	Frequency (%)
38495499.24	1	0.2%
31638205.62	1	0.2%
4109841.57	1	0.2%
3322750.38	1	0.2%
2080753.765	1	0.2%
1526431.59	1	0.2%
632264.94	1	0.2%
-2967468.45	1	0.2%
-5208626.63	1	0.2%
-6199158.928	1	0.2%

IND.COB
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	410
Distinct (%)	99.3%
Missing	70
Missing (%)	14.5%
Infinite	0
Infinite (%)	0.0%
Mean	0.3296002051

Minimum	-0.08869110907
Maximum	1.079495081
Zeros	2
Zeros (%)	0.4%
Negative	1
Negative (%)	0.2%
Memory size	3.9 KiB

Quantile statistics

Minimum	-0.08869110907
5-th percentile	0.003709156719
Q1	0.1298469255
median	0.3033047549
Q3	0.4886125866
95-th percentile	0.7808489926
Maximum	1.079495081
Range	1.168186191
Interquartile range (IQR)	0.3587656611

Descriptive statistics

Standard deviation	0.2461518329
Coefficient of variation (CV)	0.7468194166
Kurtosis	-0.1563872622
Mean	0.3296002051
Median Absolute Deviation (MAD)	0.178746173
Skewness	0.640019937
Sum	136.1248847
Variance	0.06059072485
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.6194085783	2	0.4%
0	2	0.4%
0.6779913949	2	0.4%
0.4595930557	1	0.2%
1.017504493	1	0.2%
0.7884550965	1	0.2%
0.5513657417	1	0.2%
0.1529281329	1	0.2%
0.463074152	1	0.2%
0.3134299051	1	0.2%
Other values (400)	400	82.8%
(Missing)	70	14.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-0.08869110907	1	0.2%
0	2	0.4%
5.537123642 × 10^-5	1	0.2%
0.0001201937542	1	0.2%
0.00036455723	1	0.2%
0.0003724350936	1	0.2%
0.0003849276111	1	0.2%
0.000447582127	1	0.2%
0.0004779125332	1	0.2%
0.0007338317605	1	0.2%

Value	Count	Frequency (%)
1.079495081	1	0.2%
1.07143418	1	0.2%
1.038471249	1	0.2%
1.017504493	1	0.2%
1.015026033	1	0.2%
1.014152094	1	0.2%
0.9168979511	1	0.2%
0.8895889709	1	0.2%
0.8731352897	1	0.2%
0.8729411808	1	0.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Nº	REGIÃO	UF	ENTE	ANO	N.JUR	POP	TAM.ATV	AD.PROG	C.PROG	PRT_massa	MassaSeg.	GR_POD	GR_SEGR	CIE_FISC	CIE_AUD	CIE_CRP	GI_DIV.CART	GI_C.TÉC	GI_P.INV	GI_COMITÊ	GI_CONS	SA_AMRTZ	SA_PUB.REL	SA_REPAS	SA_R.ALIQ	GTI_INV.TI	DDM_CART	DDM_ACES	DDM_ATAS	RP_REG.ENV	RP_REL.GOV	RP_SITE	PS_OUV	PS_GEST	IP_REP.CF	IP_SELEC	LI_CERT.MB	LI_DIR.CERT	R.FIN	IND.SF	R.INV	VAR.INV	R.AT	IND.COB
0	1	CO	GO	Abadia de Goiás	1998-03-26	Autarquia	8,958.00	15,368,522.77	NÃO	NaN	PEQUENO PORTE	mais favorável	1	1.00	REG	REG	IRG	REG	B	0	1	1.00	0	IRG	REG	1.00	0.00	1.00	REG	0.00	A	0.00	0.00	1.00	1.00	B	EL	C	1	1,023,035.10	1.66	2,649,065.32	0.21	-30,673,267.79	0.33
1	2	CO	GO	Abadiânia	2001-10-10	Autarquia	20,461.00	174,719.81	NÃO	NaN	PEQUENO PORTE	mais favorável	1	1.00	REG	REG	JUD	REG	C	1	0	1.00	0	JUD	REG	1.00	0.00	0.00	REG	0.00	B	0.00	0.00	1.00	0.00	C	EL	C	1	-1,570,789.26	0.53	-197,592.51	-0.53	NaN	NaN
2	3	NE	CE	Acarapé	2013-04-26	Autarquia	15,036.00	43,696.21	NÃO	NaN	PEQUENO PORTE	mais favorável	1	0.00	REG	REG	IRG	REG	C	1	0	1.00	0	REG	IRG	1.00	0.00	1.00	REG	0.00	B	0.00	1.00	0.00	0.00	B	ESC	C	1	-559,378.13	0.84	-7,724.83	-0.15	-91,387,699.63	0.00
3	4	NE	CE	Acopiara	2009-08-12	Autarquia	54,481.00	45,910,781.05	NÃO	NaN	MÉDIO PORTE	mais favorável	1	1.00	REG	REG	REG	REG	B	1	1	1.00	0	REG	REG	1.00	1.00	1.00	REG	1.00	A	1.00	1.00	1.00	0.00	A	ESC	C	1	8,183,757.08	3.21	5,722,056.29	0.14	-123,089,791.11	0.27
4	5	CO	GO	Acreúna	2005-08-22	Autarquia	22,546.00	42,459,373.90	NÃO	NaN	MÉDIO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	B	1	1	1.00	1	REG	REG	1.00	0.00	1.00	REG	1.00	A	1.00	1.00	1.00	1.00	A	EL	C	1	6,020,421.46	1.82	5,352,032.17	0.14	-131,203,244.98	0.24
5	6	S	PR	Adrianópolis	1994-07-29	Autarquia	5,857.00	8,010,256.66	NÃO	NaN	PEQUENO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	A	1	1	0.00	0	REG	REG	0.00	0.00	1.00	REG	0.00	A	0.00	1.00	0.00	1.00	C	ESC	B	0	NaN	0.00	2,029,296.80	0.34	-43,263,463.21	0.16
6	7	NE	PE	Afogados da Ingazeira	2002-08-01	Autarquia	37,404.00	405,891.32	NÃO	NaN	MÉDIO PORTE	menos favorável	1	1.00	JUD	REG	JUD	REG	B	1	1	0.00	1	JUD	JUD	0.00	0.00	1.00	REG	0.00	C	0.00	1.00	0.00	0.00	B	ESC	C	0	-5,075,837.07	0.60	307,209.40	3.11	-122,786,505.77	0.00
7	8	NE	PE	Afrânio	2001-03-28	Órgão Adm. Direta	19,810.00	28,316,185.30	NÃO	NaN	PEQUENO PORTE	mais favorável	1	1.00	REG	REG	JUD	REG	B	1	1	0.00	0	REG	REG	1.00	0.00	1.00	REG	0.00	A	0.00	1.00	0.00	0.00	A	ESC	C	0	2,875,091.88	2.30	3,712,963.12	0.15	-34,345,138.06	0.45
8	9	N	PA	Afuá	2002-06-21	NaN	39,567.00	2,592,301.75	NÃO	NaN	MÉDIO PORTE	mais favorável	1	0.00	IRG	REG	IRG	IRG	B	1	1	0.00	0	IRG	IRG	0.00	0.00	0.00	REG	0.00	C	NaN	1.00	0.00	0.00	NaN	ESC	C	0	-757,945.77	0.61	-813,289.43	-0.24	NaN	NaN
9	10	NE	PE	Agrestina	2013-06-27	Autarquia	25,065.00	4,430,202.46	NÃO	NaN	MÉDIO PORTE	mais favorável	1	0.00	REG	REG	JUD	REG	A	1	1	1.00	1	JUD	REG	1.00	0.00	0.00	REG	NaN	A	0.00	1.00	0.00	0.00	C	ESC	C	1	823,682.47	1.22	1,095,091.57	0.33	-89,869,362.10	0.05

Last rows

	Nº	REGIÃO	UF	ENTE	ANO	N.JUR	POP	TAM.ATV	AD.PROG	C.PROG	PRT_massa	MassaSeg.	GR_POD	GR_SEGR	CIE_FISC	CIE_AUD	CIE_CRP	GI_DIV.CART	GI_C.TÉC	GI_P.INV	GI_COMITÊ	GI_CONS	SA_AMRTZ	SA_PUB.REL	SA_REPAS	SA_R.ALIQ	GTI_INV.TI	DDM_CART	DDM_ACES	DDM_ATAS	RP_REG.ENV	RP_REL.GOV	RP_SITE	PS_OUV	PS_GEST	IP_REP.CF	IP_SELEC	LI_CERT.MB	LI_DIR.CERT	R.FIN	IND.SF	R.INV	VAR.INV	R.AT	IND.COB
473	474	SE	SP	Potirendaba	2005-07-14	Autarquia	17,516.00	28,626,302.33	NÃO	NaN	MÉDIO PORTE	menos favorável	1	1.00	REG	REG	IRG	REG	NaN	1	0	1.00	0	REG	REG	0.00	0.00	1.00	REG	1.00	A	0.00	1.00	1.00	1.00	A	ESC	C	1	-1,264,529.95	0.77	4,627,248.42	0.19	-85,069,649.35	0.25
474	475	S	PR	Quatro Barras	1992-06-02	Autarquia	23,911.00	64,916,581.30	NÃO	NaN	MÉDIO PORTE	mais favorável	1	1.00	REG	REG	REG	REG	B	1	1	1.00	0	REG	REG	0.00	0.00	1.00	REG	0.00	B	0.00	1.00	1.00	1.00	A	ESC	B	1	11,021,157.65	3.06	10,214,557.45	0.19	-46,980,926.29	0.58
475	476	NE	PE	Quixaba	2005-11-22	Autarquia	1,983.00	9,198,354.43	NÃO	NaN	PEQUENO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	NaN	0	0	0.00	0	JUD	REG	0.00	0.00	1.00	REG	1.00	C	1.00	1.00	1.00	1.00	A	ESC	C	0	576,304.35	1.26	1,570,096.79	0.21	-35,937,542.78	0.20
476	477	S	PR	Reserva do Iguaçu	2001-11-28	Autarquia	8,069.00	27,065,731.84	NÃO	NaN	PEQUENO PORTE	mais favorável	1	1.00	REG	REG	IRG	REG	NaN	1	0	0.00	0	REG	IRG	0.00	0.00	1.00	REG	0.00	B	0.00	1.00	1.00	1.00	B	EL	C	0	3,865,829.14	3.14	4,290,810.45	0.19	-8,478,942.79	0.76
477	478	SE	MG	Rio Acima	2002-12-26	Autarquia	10,420.00	2,495,332.62	NÃO	NaN	PEQUENO PORTE	mais favorável	1	1.00	REG	REG	IRG	REG	B	1	1	1.00	0	IRG	IRG	0.00	0.00	1.00	REG	1.00	B	0.00	1.00	1.00	1.00	C	EL	C	1	1,081,186.70	1.35	786,082.67	0.46	NaN	NaN
478	479	CO	MT	Rio Branco	2006-01-04	Fund. Dir. Púbico	413,418.00	15,543,271.78	NÃO	NaN	PEQUENO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	A	1	1	0.00	0	IRG	REG	1.00	0.00	1.00	REG	0.00	A	0.00	0.00	1.00	1.00	A	ESC	C	1	91,572,003.13	3.23	90,215,306.37	0.23	-295,511,611.22	0.62
479	480	SE	SP	Rubinéia	2002-02-28	Autarquia	3,170.00	27,215,102.96	NÃO	NaN	PEQUENO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	A	1	1	1.00	1	REG	REG	1.00	1.00	1.00	REG	1.00	A	0.00	1.00	1.00	1.00	C	ESC	B	0	922,542.93	1.42	3,948,486.53	0.17	-22,144,334.71	0.55
480	481	SE	MG	Sabinópolis	2006-08-29	Autarquia	15,416.00	23,300,846.96	NÃO	NaN	PEQUENO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	B	1	1	1.00	0	IRG	REG	1.00	1.00	1.00	REG	0.00	B	0.00	1.00	1.00	1.00	A	ESC	C	1	2,978,677.97	1.60	3,471,397.21	0.18	-46,424,138.90	0.33
481	482	SE	SP	Santa Rita do Passa Quatro	2004-10-14	Autarquia	27,600.00	143,121,440.04	NÃO	NaN	MÉDIO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	B	1	1	1.00	1	REG	REG	1.00	0.00	1.00	REG	1.00	C	1.00	1.00	1.00	1.00	B	ESC	C	1	-1,519,645.24	0.83	21,704,440.44	0.18	-30,460,061.14	0.82
482	483	S	RS	Santa Rosa	2001-01-29	Autarquia	73,575.00	258,269,174.68	NÃO	NaN	MÉDIO PORTE	menos favorável	1	1.00	REG	REG	REG	REG	A	1	1	0.00	0	REG	REG	0.00	1.00	1.00	REG	1.00	A	0.00	1.00	1.00	1.00	B	ESC	C	1	6,720,887.52	1.24	28,266,671.95	0.12	-341,449,342.36	0.43

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Other Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Latin 1 Sup

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Latin 1 Sup

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Latin 1 Sup

Common Values